Expense Tracker Project

Overview

This repository contains a "comprehensive expense tracking solution developed as one of my hobby project."

One of my hobby project architected and deployed on my Linux server. Built on clean architecture as 3 microservices, it features a .NET 8 WebAPI containerized with Docker. Supports distributed logging and tracing with Seq, metrics with Prometheus and Grafana. A Flutter app logs expenses and manages categories. The system uses RabbitMQ for messaging, Redis for caching, MongoDB for persistence, EF Core as ORM, Firebase for notifications, Azure EntraAD for auth & Blob storage for archrivals.

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Technology Stack

Frontend

Application Type	Name	Version	Details
Web	React	18.2.0	SPA
Mobile	Flutter	3.22	Android & iOS

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Backend

Backend Architecture

The project follows a microservices architecture with some components hosted in Azure.

Component	Name	Version	Details
API	.NET	8	Alpine Chiseled Ubuntu image (aspnet:8.0-jammy-chiseled) on Docker
Database	MongoDB	8.0 Preview · 2023	on Docker
Distributed Caching	Redis	7.0	on Docker
Distributed Messaging	RabbitMQ	3.13.6	on Docker
Logging & Tracing	Seq	2023.1	on Docker
	Serilog		Local logging (file)
Metrics & Monitoring	Grafana	11.0.0-preview	on Docker
	Prometheus	2.53.1 / 2024-07-10	on Docker
Cloud Storage & Archival	Azure Blob Storage		Azure
Authentication	Entra AD		Azure
CDNs	Azure CDN		Azure

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Demo Video

<iframe width="296" height="628" src="https://www.youtube.com/embed/4neii_v1MAQ" title="Demo" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin"></iframe>

Demo Screenshots

Deployment Environment

Docker Instances

Property	Value
Operating System	Ubuntu 23.04
Kernel	Linux 6.2.0-39-generic
Architecture	x86-64
Memory	8GB Physical
CPU(s)	2 vCPUs
Model name	AMD EPYC 7543P 32-Core Processor

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Other Missilenius Tools Involved

K6 Performance Tests

• The API has been load tested using K6
• Capable of serving 1000 requests in parallel
• Utilizes distributed caching for improved response times

Azure Cloud Integration

• Azure EntraAD: Handles authentication and authorization
• Azure Blob Storage: Planned for long-term data archival (cold storage)

Monitoring and Observability

• Seq: Centralized logging and tracing with OpenTelemetry integration
• Prometheus & Grafana: Real-time monitoring of API traffic and system metrics

Development Practices

• Build on Clean Architecture principle
• Containerised